Enrollment And Authentication On A Mobile Device

ABSTRACT

Systems and methods for biometric authentication are disclosed. The invention may be used to authenticate an individual. At least two enrollment templates may be obtained at different times. Later, an inquiry template may be obtained and compared to each of the enrollment templates in separate and distinct comparison operations. The match scores arising from the comparison operations may be fused to provide a composite match score. The composite match score may be compared to an acceptance range. If the composite match score is within the acceptance range, the individual may be authenticated.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority to U.S. provisionalpatent application Ser. No. 62/029,265, filed Jul. 25, 2014 and to U.S.provisional patent application Ser. No. 62/038,780, filed Aug. 18, 2014.

FIELD OF THE INVENTION

The disclosure relates to devices, systems and methods of enrolling,authenticating and verifying an individual.

BACKGROUND OF THE INVENTION

Biometric sensors for mobile devices, including fingerprint sensors, arebecoming increasingly smaller. A primary driving force toward smallerbiometric sensors comes from the popularity of mobile electronic devicessuch as smart phones. Since mobile electronic devices are limited insize, components such as fingerprint sensors must also be small.Furthermore, as more components are incorporated into a mobileelectronic device and the overall size of that mobile device does notincrease, the components must be reduced in size in order to fit withinsize constraints of the mobile device.

For purposes of describing the invention, this document will focus onfingerprint sensors, but the invention is not limited to this smallsubset of biometric sensors. Traditional fingerprint sensors that cancapture an entire finger typically have an active image area of about1″×1″. However, capture sizes of fingerprint sensors for smart phonesare generally much smaller, with active image areas on the order ofabout 15 mm×6 mm, 9 mm×4 mm, 8 mm×3 mm, 5 mm×5 mm, and smaller. As such,the fingerprint sensor on a smart phone or mobile device may often imageonly a small portion of a fingerprint (e.g. a friction-ridge surface ofa finger).

Since the active area of a fingerprint sensor is often much smaller thana finger, the finger can be placed over the sensor in a variety oforientations and positions. If the fingerprint template information(also referred to as a template) generated from an acquired fingerprintimage obtained during an enrollment process does not closely match thetemplate obtained from the fingerprint at the time of inquiry, thefingerprint matching component of the mobile electronic device may failto properly identify or verify a user. When the fingerprint matchingcomponent fails to properly verify the user, the component may falselyreject the user as being unauthorized for the desired task (which mayinclude unlocking or otherwise using the mobile device).

It should be noted that the actual fingerprint image may not be matchedto another fingerprint image. Rather, a template having informationabout a fingerprint may be created by a feature extraction process, andthe templates may be compared to one another in order to determinewhether a match exists. Matching processes may utilize, for example,minutiae-matching or pattern-matching (a.k.a. keypoint-matching)procedures. Fingerprint templates may contain information, for example,about minutiae points or keypoints within a fingerprint image.

Attempts have been made to reduce the false rejection rate. One of themore popular solutions involves obtaining multiple templatescorresponding to images of the finger at the time of enrollment. Duringthe enrollment process, the user is asked to place a finger on thefingerprint sensor repeatedly, for example, 10 to 15 times. After eachplacement, the user is asked to move his/her finger “slightly” before asubsequent image is taken. This “stitched enrollment” process can befrustrating for the user.

The goal of this stitching technique is to create a full size enrollmentimage by stitching together multiple smaller images. However, in orderfor this stitching technique to yield the desired benefits, the usermust place his/her finger on the fingerprint sensor in such a manner asto have new ridge structure imaged by the sensor that was not previouslyimaged during the enrollment process, but still have enough overlap withthe previous image so as to allow the fingerprint matching component tocorrelate the two images (i.e. stitch the images together). The desiredamount of overlap does not always occur, thereby undermining the abilityof the system to properly identify those who have enrolled. Improvementsto the speed and accuracy of enrolling and validating a user of a mobiledevice are therefore desired, particularly for sensors with a smalleractive area.

SUMMARY OF THE INVENTION

Embodiments for a method of authenticating an individual are disclosed.If the individual is authenticated, then the individual may be allowedto engage in an activity such as accessing a database, using a computer,entering a building, or accessing a software application running on amobile device.

In one such method, an enrollment biometric object (i.e. a biometricobject provided for the purpose of enrolling a user into anauthentication system) such as a friction-ridge surface of a finger, maybe scanned at a first time to produce a first enrollment template. Theenrollment biometric object may be moved, and the enrollment biometricobject may be scanned a second time to produce a second enrollmenttemplate. At a later time, an inquiry biometric (i.e. a biometricobject, which may be the same type or the same object as the enrollmentbiometric object that is provided for the purpose of being authenticatedby an authentication system) may be scanned in order to provide aninquiry template at a third time. Scanning may be carried out by anultrasonic sensor. In some implementations, an ultrasonic or capacitivearea-array sensor may be used for scanning purposes.

A first match score may be produced by comparing the inquiry templatewith only the first enrollment template, and a second match score may beproduced by comparing the inquiry template with only the secondenrollment template. The match scores may be mathematically fused inorder to produce a composite match score, and the composite match scoremay be compared to an acceptance range. If the composite match score iswithin the acceptance range, then the individual may be authenticated.

Mathematically fusing the match scores may include multiplying each ofthe match scores by a weighting factor to provide a weighted matchscore, and adding the weighted match scores to produce a composite matchscore. The weighting factor may be based on a quality value associatedwith the enrollment template. In some implementations, the quality valueassociated with the enrollment template may be based on image contrastdetermined during an enrollment process. In some implementations, thequality value associated with the enrollment template may be based on asignal-to-noise ratio determined during an enrollment process, or thequality of the enrollment template may be assessed based on how much theinquiry template overlaps with the enrollment template.

One embodiment is a system including one or more biometric sensors, adatabase in communication with at least some of the sensors, and one ormore programmed computers or processors that are in communication withthe database and possibly one or more of the sensors. The computer orprocessor may be programmed to carry out the method described above.

More generally speaking, one embodiment of a system has

-   -   (a) a means for scanning a portion of a friction-ridge surface        of an enrollment finger at a first time to produce a first        enrollment template, and at a second time to produce a second        enrollment template;    -   (b) a means for scanning a portion of a friction-ridge surface        of an inquiry finger at a third time to produce an inquiry        template;    -   (c) a means for producing a first match score by comparing the        inquiry template with the first enrollment template and for        producing a second match score by comparing the inquiry template        with the second enrollment template;    -   (d) a means for mathematically fusing the match scores to        produce a composite match score;    -   (e) a means for comparing (which may be a programmed computer)        the composite match score to an acceptance range; and    -   (f) means for authenticating (which may be a programmed        computer) the individual if the composite match score is within        the acceptance range.

The means for scanning a portion of a friction-ridge surface of theenrollment finger or the means for scanning a portion of afriction-ridge surface of the inquiry finger may be an area-arraysensor. The means for scanning a portion of a friction-ridge surface ofthe enrollment finger or the means for scanning a portion of afriction-ridge surface of the inquiry finger may be an ultrasonicsensor.

The means for mathematically fusing the match scores may multiply atleast one of the match scores by a weighting factor to provide aweighted match score. The means for mathematically fusing the matchscores may determine the weighting factor based on a quality valueassociated with the enrollment template.

One embodiment, which may be used to program the computer mentionedabove, may be a non-transitory computer-readable storage medium havingstored thereon instructions for carrying out a method described herein.The instructions may cause a computer to:

-   -   (a) scan a portion of a friction-ridge surface of an enrollment        finger at a first time to produce a first enrollment template;    -   (b) scan a portion of a friction-ridge surface of the enrollment        finger at a second time to produce a second enrollment template;    -   (c) scan a portion of a friction-ridge surface of an inquiry        finger at a third time to produce an inquiry template;    -   (d) produce a first match score by comparing the inquiry        template with the first enrollment template;    -   (e) produce a second match score by comparing the inquiry        template with the second enrollment template;    -   (f) mathematically fuse the match scores to produce a composite        match score;    -   (g) compare the composite match score to an acceptance range;        and    -   (h) authenticate the individual if the composite match score is        within the acceptance range.

The instructions on the non-transitory computer-readable storage mediummay cause the computer to instruct an area-array sensor to carry outscanning of a portion of a friction-ridge surface of the enrollmentfinger or the inquiry finger. The instructions on the non-transitorycomputer-readable storage medium may cause the computer to instruct anultrasonic sensor to scan a portion of a friction-ridge surface of theenrollment finger or the inquiry finger.

The instructions on the non-transitory computer-readable storage mediummay cause the computer to mathematically fuse the match scores bymultiplying at least one of the match scores by a weighting factor toprovide a weighted match score.

The instructions on the non-transitory computer-readable storage mediummay cause the computer to determine the weighting factor based on aquality value associated with the enrollment template.

BRIEF DESCRIPTION OF THE DRAWINGS

For a fuller understanding of the nature and objects of the invention,reference should be made to the accompanying drawings and the subsequentdescription. The disclosure will now be described by way of non-limitingexamples, with reference to the attached drawings and diagrams.

FIG. 1A illustrates a flow diagram depicting a method of authenticatingan individual.

FIGS. 1B and 1C are graphical representations of a method described inFIG. 1A.

FIG. 2 depicts a system for authenticating an individual including acomputer, a database and a biometric sensor.

FIG. 3 depicts a system for authenticating an individual including acomputer, a database and one or more enrollment and/or inquiry sensors.

FIG. 4 illustrates an exemplary implementation of enrollment of a user'sfingerprint images according to aspects of the present disclosure.

FIG. 5 illustrates an exemplary implementation of validation of a user'sfingerprint image(s) according to aspects of the present disclosure.

FIG. 6 illustrates another implementation of enrollment of a user'sfingerprint images according to aspects of the present disclosure.

FIG. 7 illustrates another implementation of validation of a user'sfingerprint image(s) according to aspects of the present disclosure.

FIG. 8A illustrates an example of a set of fingerprint images stored ina template repository and FIG. 8B illustrates examples of rejectedfingerprint images that may not be added to the template repositoryaccording to aspects of the present disclosure.

FIG. 9 illustrates an exemplary block diagram of a device that may beconfigured to implement methods of interactive user fingerprintauthentication according to aspects of the present disclosure.

FIG. 10A illustrates an exemplary flow chart for implementing methods ofinteractive user fingerprint authentication, FIG. 10B illustrates anexemplary flow chart for implementing methods of determining a status offingerprint authentication, and FIG. 10C illustrates another exemplaryflow chart for implementing methods of determining a status offingerprint authentication according to aspects of the presentdisclosure.

DETAILED DESCRIPTION OF THE DISCLOSURE

One embodiment includes a method of authenticating an individual (e.g. ahuman being) by obtaining and storing at least two enrollment templates,and at a later time comparing each of those enrollment templates to aninquiry template in separate comparison operations. Each enrollmenttemplate describes a biometric object (e.g. a friction-ridge surface ofa finger) of the individual, who may desire to be authenticated at alater date. In contrast to the enrollment template, the inquiry templatedescribes a biometric object (e.g. a friction-ridge surface of a finger)of an individual that desires to be authenticated, who may or may not bethe same individual that provided the biometric object for theenrollment templates. The enrollment templates and the inquiry templatemay each be a computer-readable file that has information about thebiometric objects from which these files were generated. These files may(but need not) include enough information to generate an image of thebiometric object via a display monitor.

In some implementations, the information contained in the enrollmenttemplates is not combined with information in other enrollmenttemplates. For example, the enrollment templates may not includetemplate information from enrollment images that have been stitchedtogether to create a larger, more “representative” template of thefingerprint than would otherwise be possible based solely on the sensorsize. Rather, each enrollment template may be treated and usedindependently from other enrollment templates. When the individualdesires to be authenticated, an inquiry template may be obtained fromthe individual, and the inquiry template may be compared separately toeach of the enrollment templates. For example, features found in theinquiry template may be compared to features found in an enrollmenttemplate, and the degree of similarity between these features may bedetermined in order to assess whether the inquiry template and theenrollment template can be declared to match one another. The degree ofsimilarity may be quantified and represented as a match score. As such,the match score may indicate how similar the enrollment template is tothe inquiry template. In some implementations, two or more imagesacquired during an enrollment process may be stitched together to formany one of the enrollment templates. In a hybrid approach, one or moreenrollment templates based on stitched images and one or more templatesbased on un-stitched (e.g. single) images may be used in thematching/verification process.

By comparing the inquiry template to each of the enrollment templates, amatch score may be generated from information produced by each of thecomparisons. Consequently, a match score may be generated for each ofthe enrollment templates. The match scores may be mathematically fusedto produce a composite match score. The composite match score may beassociated with the inquiry template that was used to produce the matchscores.

An acceptance range may be identified and compared with the compositematch score in order to assess whether an individual should beauthenticated. For example, the composite match score may be compared tothe acceptance range, and if the composite match score is within theacceptance range, the individual may be authenticated. However, if thecomposite match score is not within the acceptance range, the individualmay not be authenticated.

Once authenticated, the individual may be permitted to engage in anactivity that is permitted for those that have been authenticated. Forexample, an authenticated individual may be permitted to access acomputer database, use a computer, use a mobile electronic device,access or otherwise use a software application running on a mobiledevice, or enter a building.

Although many types of biometric objects may be used in conjunction withthis invention, one particularly useful biometric object is thefriction-ridge surface of a finger. Each of the enrollment templates andthe inquiry template may be obtained by scanning a portion of thefriction-ridge surface of a finger. One or more ultrasonic fingerprintsensors, which may be area-array sensors, may be used for this purpose.An example of an ultrasonic area-array sensor that is suitable for thispurpose is described in U.S. Pat. No. 7,739,912 entitled “UltrasonicFingerprint Scanning Utilizing a Plane Wave”.

Having provided a general overview of a method for authenticating auser, additional details are now provided. The figures are used alongwith the following text in order to better communicate features that arein keeping with the invention.

The enrollment templates may be obtained at different times from anenrollment biometric object, such as a finger. That is to say that theenrollment templates may be obtained during different scanningoperations, such as during successive scans of an enrollment session.Movement of the enrollment biometric object between scanning operationsis permitted, and may be beneficial. For instance, the individualproviding the enrollment biometric object may be instructed to move theenrollment biometric object after a first scanning operation iscomplete, and before a second scanning operation commences. In thismanner, the enrollment templates will likely not be highly similar toone another. However, it should be noted that two or more enrollmenttemplates may be highly similar, or even identical.

With reference to FIGS. 1A, 1B and 1C, a first enrollment template maybe obtained by scanning 10 a portion of a friction-ridge surface of anenrollment finger at a first time during which a first scanningoperation occurs. The enrollment finger may be moved 13 relative to thesensor, and a second enrollment template may be obtained by scanning 16a portion of the friction-ridge surface of the enrollment finger at asecond time during a second scanning operation. The first and secondenrollment templates may image different parts of the friction-ridgesurface. Thus, in some instances, the first and second enrollmenttemplates may or may not image overlapping parts of the friction-ridgesurface. Although only two enrollment templates are identified in thedescription above, more enrollment templates may be obtained and used.That is to say, the invention is not limited to collecting and comparingmerely two enrollment templates—instead, at least two enrollmenttemplates will be collected, but more may be collected and used, ifdesired, for a single individual. For example, in some implementations,three, four, five, six, seven, eight or more enrollment templates may begenerated of a finger during an enrollment session. In someimplementations, an angle or direction of the finger with respect to theactive area of the sensor may be cued to the user during enrollment toacquire various enrollment templates at a variety of angles. The cuedangle or direction of the finger may be stored with the templateinformation for each template, for example, as cued orientation-anglemetadata associated with the template.

After the set of enrollment templates are obtained and the enrollmentprocess is complete, the individual may desire to be authenticated. Inorder to be authenticated, the individual may present a biometric objectat a third time (herein, this biometric object is called the “inquirybiometric object”) during which a third scanning operation occurs 19 inorder to produce the inquiry template corresponding to the inquirybiometric object. While enrollment templates may be generated 10, 16during an enrollment phase, the third scanning operation 19 may occurduring an authentication/verification phase. The inquiry biometricobject may or may not be the same biometric object that was presentedduring enrollment. The inquiry template may be compared 22, 25 to eachof the enrollment templates during separate comparison operations, whichmay be carried out at the same time or at different times. Eachcomparison operation 22, 25 may produce a match score, which isindicative of the degree to which the inquiry template matches theenrollment template. A comparison may be made between all of theenrollment templates and the inquiry template, or comparisons may bemade between a proper subset (i.e. less than all of the enrollmenttemplates for the individual) of the enrollment templates and theinquiry template.

The match scores, each of which corresponds to a comparison of theinquiry template and at least one of the enrollment templates, may bemathematically fused 28 in order to produce a composite match score.Fusing the match scores may be accomplished merely by adding the matchscores together to determine a sum. However, it is believed that abetter manner of fusing the match scores involves multiplying each matchscore by a weight in order to produce a weighted match score, and thenadding the weighted match scores in order to produce the composite matchscore. In this manner, the enrollment templates that have higher weightswill be more influential with regard to the composite match score, andthose enrollment templates that have lower weights will be lessinfluential with regard to the composite match score. In someimplementations, the weighting factor may be based on a degree ofoverlap between the inquiry template and one or more of the enrollmenttemplates. For example, a larger weighting factor may be determinedbetween an inquiry template and an enrollment template when the templateinformation indicates a higher level of overlap between the templateinformation associated with each of the templates (e.g. with nearlyidentical enrollment and inquiry images), whereas a lower weightingfactor may be determined when little or no overlap occurs between thetemplate information. When the weighting factor between an inquirytemplate and any of the enrollment templates is higher, the accuracy ofthe composite match score may also be higher and the likelihood ofdetermining a correct match increases.

A weight for each enrollment template may be determined based oncriteria that is designed to reflect the ability of an enrollmenttemplate to accurately authenticate an individual. For example, if someof the enrollment templates are believed to be higher in quality thanother enrollment templates, then the higher-quality enrollment templatesmay be associated with higher weights and the lower-quality enrollmenttemplates may be associated with lower weights. One or more qualityvalues may be associated with each enrollment template. In someimplementations, the quality of each enrollment template may be assigneda quality value that is based on image contrast determined during theenrollment process. In some implementations, the quality of eachenrollment template may be assigned a quality value that is based on asignal-to-noise ratio determined during the enrollment process. Forexample, an enrollment template having a higher image contrast or highersignal-to-noise ratio may be given a weight that is higher than otherenrollment images that have a lower image contrast or a lowersignal-to-noise ratio. Or, the quality of the enrollment template may beassessed based on how much the inquiry template overlaps with theenrollment template. In some implementations, the quality value based onimage contrast may be determined from an acquired enrollment image bysubtracting the signal levels of a plurality of ridge regions from thesignal levels of a plurality of valley regions prior to storing thetemplate. In some implementations, the quality value based on asignal-to-noise ratio may be determined by generating a ratio betweenthe largest signals in a scanned region of the finger and an averagebackground signal (e.g. without ultrasonic energy applied during imageacquisition) of an acquired enrollment image. In some implementations,the quality value based on the degree of overlap may be determined bycalculating the fractional area in one template that is contained inanother template. In some implementations, one or more quality valuesmay be stored with the template information for each template, forexample, as quality metadata associated with the template. In someimplementations, a low quality value or quality score may cause anenrollment template to be discarded and replaced by an enrollmenttemplate with a higher quality score. For example, a user may beinstructed to re-position a finger on the sensor during an enrollmentphase to generate or produce a substitute enrollment template.

Once mathematical fusing and production of the composite match score 28corresponding to an inquiry template are completed, the composite matchscore may be compared 31 to an acceptance range. The acceptance rangemay be selected so as to authenticate those individuals who should beauthenticated, but deny authentication to those individuals who shouldnot be authenticated. That is to say that with some experience, it willbecome known that composite match scores in a particular range of valuesgenerally correspond to individuals that should be authenticated, andthat composite match scores outside that range generally correspond toindividuals that should not be authenticated. For example, theacceptance range may be set so as to authenticate individuals havingcomposite match scores at or above a certain value, while denyingauthentication to those individuals having composite match scores belowthat value. In some implementations, an acceptance threshold value maydefine the authentication range, such that composite match scores abovethe acceptance threshold value allows a user to be authenticated whilecomposite match scores below the acceptance threshold value prevents theuser from being authenticated. In some implementations, the acceptancerange may be a user-dependent acceptance range. For example, theacceptance threshold value may be adjusted or otherwise adapted toaccommodate users with difficult-to-image fingers or users with minimalfingerprint ridges. In some implementations, a user-dependent acceptancethreshold value may be stored as acceptance threshold value metadataalong with other template information in each template.

In some embodiments, the enrollment process may be completed withoutstitching enrollment templates or acquired image data together. Suchstitching operations may be difficult, costly and frustrating for theindividual during the enrollment process. By offering the ability tocomplete enrollment without stitching, an individual that desires to beenrolled may be enrolled more quickly since there is no need to obtainimages that overlap. Furthermore, it is possible that the enrollmentprocess may be completed by obtaining as few as two enrollmenttemplates, and none of the enrollment templates need have overlappingportions. That is to say, when obtaining information about the biometricobject used to enroll an individual into an authentication system, theimages of that biometric object may be obtained without regard towhether one image overlaps with another image. Consequently, anindividual that desires to be enrolled in an authentication system maybe enrolled more quickly through use of fewer enrollment templates,and/or the enrollment process may be completed more quickly and withless computing time since a stitched image is not required. In someimplementations, the enrollment templates may be matched one by one withan inquiry template, fused, and an intermediate composite match scoregenerated. In this manner, if a sufficiently high composite match scoreis generated with only a subset of the stored enrollment templates, thena potential user may be authenticated without use of all the storedtemplates, thus saving time, improving latency, reducing power, andallowing a user quicker access. Note that in this approach, anintermediate composite matching score may be sufficient while matchingwith as few as one stored template. In some implementations, the orderof template matching may be improved to reduce latency by placing thetemplates with the highest quality value or those most-oftensuccessfully matched to a user early in the order. The order of templatematching may evolve over time as more authentication/verificationprocesses for a specific user are successfully completed.

FIG. 2 is a block diagram illustrating a system 100 for authenticatingan individual. One such system has one or more biometric sensors 103, atleast one database 106 with a memory having the ability to storeinformation, at least one computer or processor 109, and communicationslinks 112 that may be provided between some or all of these components103, 106, and 109. FIG. 2 depicts a system 100 including a computer orprocessor 109, a database 106, and a single biometric sensor 103, andFIG. 3 depicts a system 100 including one or more enrollment and/orinquiry sensors 103. The sensors 103 may each be an area-array sensor.The sensors 103 may each be an ultrasonic area-array sensor. In theimplementation shown in FIG. 2, the biometric sensor 103 may serve bothas the enrollment sensor and as the inquiry sensor, such as may be foundin a mobile device. When more than one sensor 103 is used in system 100as shown in FIG. 3, one or more of the sensors 103/ES may be used forenrolling individuals to obtain enrollment templates from an enrollmentbiometric (such as an enrollment finger), and others of the sensors103/IS may be used to obtain inquiry templates from an inquiry biometric(such as an inquiry finger) in a distributed system. The enrollmenttemplates and inquiry templates may include information data setsdescribing features of a friction-ridge surface of the enrollmentfinger, and the inquiry biometric may include an information data setdescribing features of a friction-ridge surface of the inquiry finger.

The system 100 may include a database 106 that is in communication withat least the enrollment biometric sensors 103/ES, and possibly theinquiry biometric sensors 103/IS. In some implementations, the database106 may be a remote database. In some implementations, a local memorysuch as a memory in a secure portion of a local processor may beconfigured to hold the database and may contain the template informationsuch as the enrollment templates and the inquiry template. The database106 may be referred to as a template repository elsewhere in thisdisclosure. The system 100 may include a computer 109 that is incommunication with the database 106, and possibly the inquiry biometricsensors 103/IS. The database 106 may be used to store enrollmenttemplates (and possibly inquiry templates) that may be used by thecomputer 109 during an authentication procedure, such as those describedabove. The computer 109 may be programmed to produce at least a firstmatch score by comparing an inquiry template with a first enrollmenttemplate, and to produce a second match score by comparing the inquirytemplate with a second enrollment template. In addition, the computer109 may be programmed to mathematically fuse the match scores (which maybe weighted match scores) to produce a composite match score, and thencompare the composite match score to an acceptance range. Theprogramming of the computer 109 may be such that if the computer 109determines that the composite match score is within the acceptancerange, then the computer 109 may provide an indication authenticatingthe individual.

Some fingerprint sensors may have sufficient active area to image anentire fingerprint with a single scan. More recently, the active area ofbutton-based fingerprint sensors such as those from some of thepremium-tier cell phone manufacturers is much reduced in size yetsquare. Some ultrasonic fingerprint sensors are rectangular with activeareas such as 4 mm×9 mm or 3 mm×8 mm to allow inclusion in rectangularbuttons or to fit in the small region behind a cover glass and below adisplay area of a mobile device, such as a cell phone. Sensors withsquare or rectangular active areas may be required in order to correctlymatch and validate users that have enrolled their fingers with themobile device, even if a user wishes to position their fingers at widelyvarying angles with respect to the device while being authenticated.Current enrollment policies may require the user to enroll a fingerwhile positioning the finger with essentially the same angle duringimage acquisition. It is desirable to allow verification of an enrolleduser in order to gain access to a mobile device with whatever rotationangle the user desires (e.g. +/−45 degrees, +/−60 degrees, +/−90degrees, 180 degrees or other angle) without reducing the accuracy andspeed at which the user can be verified.

To improve finger enrollment and matching/verification sequences withfingerprint sensors having small, rectangular active areas for use insmall, rectangular home buttons and authenticating fingerprint sensorsat the bottom of cell phones, enrollment may be done with the fingerrotating with respect to the sensor while images of the finger areacquired. A user may be instructed by the enrollment application toplace the finger in various, pre-specified positions (e.g. 0, +/−45 and+/−90 degrees). This is in contrast to systems that enroll fingers in asingle position (i.e. a vertical position) and then attempt to match atdifferent angles. A problem using a single direction for the finger on arectangular sensor is that enrollment may result in minimal overlapbetween an enrolled image (e.g. a template) and a match attempt,potentially resulting in a low matching score and therefore increasingthe possibility that an authorized user will not be verified and thusdenied access to his/her cell phone. Reducing match thresholds to allowfor low matching scores potentially allows an imposter to gain access tothe system and is therefore undesirable. Allowing for and requestingrotation of the finger during enrollment as proposed here mitigates thisproblem by ensuring sufficient fingerprint area is captured duringenrollment so as to allow subsequent matching at different angles (e.g.at any angle 0 through 360 degrees) and to have a minimal angledifference between at least one of the enrolled images. Increasing theoverlap between enrolled and matched images improves the false acceptratio (FAR) while reducing the false reject ratio (FRR). In someimplementations, the enrollment templates may be augmented with anenrollment-data field (i.e., metadata) indicating the offset anglerequested of the user during enrollment of a finger (e.g. 0, +/−45 or+/−90 degrees). For example, the cued angled or finger direction may bestored as metadata with each template. Additionally, an adaptivetechnique may be employed by the matching sequence to compile a list offinger orientation angles generally used by the enrolled user duringverification, and to use this list along with the cued orientation-anglemetadata as specified in the corresponding enrollment-data field toguide the matching/verification sequence on which stored template(s) toattempt to match first, resulting in potentially higher accuracy andlower latency.

FIG. 4 illustrates an exemplary implementation of enrollment of a user'sfingerprint images according to aspects of the present disclosure. Asshown in FIG. 4, in block 202, the method captures a fingerprint image.In block 204, the method extracts feature keypoints from the fingerprintimage captured. In block 206, the method checks the coverage anddistributions of the feature keypoints with respect to the fingerprintimage captured. If there is sufficient coverage of the fingerprint imageby the feature keypoints (206_Yes), the method moves to block 208.Alternatively, if there is insufficient coverage of the fingerprintimage by the feature keypoints (206_No), the method moves to block 228.In block 208, the method extracts descriptions of the feature keypointsof the fingerprint image.

In block 210, the method determines whether the fingerprint imagecaptured is a first valid fingerprint image. If the fingerprint imagecaptured is a first valid fingerprint image (210_Yes), the method movesto block 212. On the other hand, if the fingerprint image captured isnot a first valid fingerprint image (210_No), the method moves to block214. In block 212, the method adds the template of the fingerprint imageto a template repository 222, and then moves to block 228.

In block 214, the method attempts to match the template of fingerprintimage captured with one or more templates of images in the templaterepository 222; it then moves to block 216. In block 216, the methoddetermines whether there is a match between the template of fingerprintimage captured and the templates of one or more images in the templaterepository 222. If there is a match (216_Yes), the method moves to block224. Otherwise, if there is not a match (216_No), the method moves toblock 218.

In block 218, the method determines whether the number of templates(descriptions of the fingerprint images) associated with a user'sfingerprint in the template repository 222 exceeds a minimum number oftemplates. In some implementations, a template may include at least oneof: 1) descriptions of feature keypoints; 2) minutiae template; 3)pattern matching template; or any combination thereof. If the number oftemplates exceeds a minimum number of templates (218_Yes), the methodexits the enrollment phase (also referred to as the template repositorycollection phase) and moves to a fingerprint inquiry validation phase,which is described below in association with FIG. 5. Alternatively, ifthe number of templates does not exceed a minimum number of templates(218_No), the method moves to block 220. In block 220, the method addsthe template of the fingerprint image to the template repository 222,and then moves to block 228.

In block 224, the method discards the overlapped (matched) fingerprintimage. In block 226, the method determines whether the overlappedfingerprint image is matched on correct angle. Whether the overlappedfingerprint image is matched on correct angle or not, in both situationsthe method moves to block 228, but different feedback messages and/orinstructions may be provided to the user depending on the outcome ofwhether the overlapped fingerprint image is matched on the correctangle.

In block 228, the method provides feedback to the application layer, andthen it may move to one or more of the blocks 230, 232, and/or 234. Inblock 230, the application layer may direct the user to align finger inproper orientation in the event of the overlapped fingerprint image isnot matched on correct angle. Then, the method may move back to block202. In block 232, the application layer may direct the user to move thefinger in the event of the overlapped fingerprint image is matched oncorrect angle. In addition, the application layer may direct the user tomove the finger to get a better coverage of the sensor area as in thecase when there is insufficient coverage of the fingerprint image by thefeature keypoints as determined in block 206. After block 232, themethod moves back to block 202. In block 234, the application layer mayprovide an update of the enrollment progress to the user. For example,if a template of a fingerprint image is successfully added to thetemplate repository 222, a forward progress may be shown to the user. Onthe other hand, if the method cannot use the fingerprint image captured,for example due to insufficient coverage by the feature keypoints, thenthe progress bar (not shown) may not advance or a negative progress maybe shown to the user. After block 234, the method moves back to block202.

FIG. 5 illustrates an exemplary implementation of validation of a user'sfingerprint image(s) according to aspects of the present disclosure. Inthe exemplary implementation shown in FIG. 5, in block 302, the methodcaptures a fingerprint image. In block 304, the method extracts featurekeypoints from the fingerprint image captured. In block 306, the methodchecks the coverage and distributions of the feature keypoints withrespect to the fingerprint image captured. If there is sufficientcoverage of the fingerprint image by the feature keypoints (306_Yes),the method moves to block 308. Alternatively, if there is insufficientcoverage of the fingerprint image by the feature keypoints (306_No), themethod moves to block 322. In block 308, the method extractsdescriptions of the feature keypoints of the fingerprint image.

In block 310, the method attempts to match the template of fingerprintimage captured with one or more templates of images in a templaterepository 330; it then moves to block 312. In block 312, the methoddetermines whether there is a match between the template of fingerprintimage captured and the one or more templates of images in the templaterepository 330. If there is a match (312_Yes), the method moves to block316. Otherwise, if there is not a match (312_No), the method moves toblock 314.

In block 316, the method discards the overlapped (matched) fingerprintimage, and checks for consecutive matches. In block 318, the methodcounts the number of consecutive matches (for example 5 consecutivematches). Note that in some implementations, instead of checking forconsecutive matches, the method may check for a percentage of matches inblock 316 and may count the percentage of matches (such as 80% ofmatches) among a plurality of checks in block 318.

In block 320, the method determines whether the matching exit criteriahave been met. Whether the matching exit criteria have been met or not,in both situations the method moves to block 322, but different feedbackmessages and/or instructions may be provided to the user depending onthe outcome of whether the matching exit criteria have been met.

In block 314, the method sorts the templates in the template repository330. In block 324, the method determines whether the fingerprint imageis a better template than the existing templates of images in thetemplate repository 330. If the fingerprint image is a better templatethan at least one of the existing templates of images in the templaterepository 330 (324_Yes), the method moves to block 328. Alternatively,if the fingerprint image is not a better template than at least one ofthe existing templates of images in the template repository 330(324_No), the method moves to block 326.

In block 326, the method determines whether the number of templatesassociated with a user's finger in the template repository has exceededa maximum number of templates. If the number of templates has exceeded amaximum number of templates (326_Yes), the method moves to block 322. Onthe other hand, if the number of templates has not exceeded a maximumnumber of templates (326_No), the method moves to block 328. In block328, the method replaces the worst template in the template repository330 with the template of the fingerprint image, which is considered as anew template. The method then moves to block 322.

In block 322, the method provides feedback to the application layer, andthen it may move to one or more of the blocks 332, 334, 336, and/or 338.In block 332, the application layer may direct the user to align fingerin proper orientation. Then, the method may move back to block 302. Inblock 334, the application layer may direct the user to move the fingerto get a better coverage of the sensor area as in the case when there isinsufficient coverage of the fingerprint image by the feature keypointsas determined in block 306. After block 334, the method moves back toblock 302. In block 336, the application layer may provide an update ofthe enrollment and/or validation progress to the user. For example, ifthe number of consecutive matches or the percent of matches meets thematching exit criteria, a forward progress may be shown to the user. Onthe other hand, if the method cannot use the fingerprint image captured,for example due to insufficient coverage by the feature keypoints or dueto the maximum number of templates in the template repository has beenexceeded, then the progress bar (not shown) may not advance or anegative progress may be shown to the user. After block 336, the methodmoves back to block 302. In block 338, the user may be notified that theenrollment and/or validation have been completed.

FIG. 6 illustrates another implementation of enrollment of a user'sfingerprint images according to aspects of the present disclosure. Inthe example shown in FIG. 6, in block 402, the method captures afingerprint image. In block 404, the method determines whether thefingerprint image captured is acceptable. In some implementations, themethods performed in blocks 204 and 206 of FIG. 4 may be performed inblock 404. If the fingerprint image captured is acceptable (404_Yes),the method moves to block 406. Otherwise, if the fingerprint imagecaptured is not acceptable (404_No), the method moves to block 414.

In block 406, the method compares the template of the fingerprint imagewith one or more templates of the images stored in the templaterepository 418. In some implementations, the methods performed in blocks208 and 214 of FIG. 4 may be performed in block 406. In block 408, themethod determines whether to update the template repository 418 with thetemplate of the fingerprint image. In some implementations, the methodsperformed in blocks 210, 216, and 218 of FIG. 4 may be performed inblock 408. If it is determined to update the template repository 418with the template of the fingerprint image (408_Yes), the method movesto block 410. Alternatively, if it is determined not to update thetemplate repository 418 with the template of the fingerprint image(408_No), the method moves to block 412.

In block 410, the method updates the template repository 418 with thetemplate of the fingerprint image. In some implementations, the methodsperformed in blocks 212 and 220 of FIG. 4 may be performed in block 410.In block 412, the method determines whether the enrollment (alsoreferred to as the template repository collection phase) has beencompleted. In some implementations, the method performed in block 218 ofFIG. 4 may be performed in block 412. If the enrollment has beencompleted (412_Yes), the method ends in block 416. Otherwise, if theenrollment has not been completed (412_No), the method moves to block414.

In block 414, the method provides feedback about the status of theenrollment progress to the user, and then moves to block 402. In someimplementations, the methods performed in blocks 228, 230, 232, and/or234 of FIG. 4 may be performed in block 414. For example, the method mayprovide feedback to the user through an application layer. Theapplication layer may direct the user to align finger in properorientation in the event of the overlapped fingerprint image is notmatched on correct angle. In addition, the application layer may directthe user to move the finger in the event of an overlapped fingerprintimage is matched on correct angle. The application layer may also directthe user to move the finger to get a better coverage of the sensor areaas in the case when the fingerprint image is not acceptable asdetermined in block 404. Moreover, the application layer may provide anupdate of the enrollment progress to the user. After a fingerprint imagehas been successfully added to the template repository 418, a forwardprogress may be shown to the user. On the other hand, if the fingerprintimage is not acceptable as determined in block 404, for example due toinsufficient coverage by the feature keypoints, then the progress bar(not shown) may not advance or a negative progress may be shown to theuser.

FIG. 7 illustrates another implementation of validation of a user'sfingerprint image(s) according to aspects of the present disclosure. Asshown in FIG. 7, in block 502, the method captures a fingerprint image.In block 504, the method determines whether the fingerprint imagecaptured is acceptable. In some implementations, the methods performedin blocks 304 and 306 of FIG. 5 may be performed in block 504. If thefingerprint image captured is acceptable (504_Yes), the method moves toblock 506. Otherwise, if the fingerprint image captured is notacceptable (504_No), the method moves to block 514. In block 506, themethod compares the template of the fingerprint image with the templatesof the one or more images stored in the template repository 518. In someimplementations, the methods performed in blocks 308 and 310 of FIG. 5may be performed in block 506.

In block 508, the method determines whether the fingerprint matchingcriteria have been met. In some implementations, the methods performedin block 312 of FIG. 5 may be performed in block 508. If the fingerprintmatching criteria have been met (508_Yes), the method moves to block510. On the other hand, if the fingerprint matching criteria have notbeen met (508_No), the method moves to block 513.

In block 510, the method determines whether to update the templaterepository 518 with the fingerprint image. In some implementations, themethods performed in blocks 314, 324, and 326 of FIG. 5 may be performedin block 510. If it is determined to update the template repository 518with the template of the fingerprint image (510_Yes), the method movesto block 512. Alternatively, if it is determined not to update thetemplate repository 518 with the template of the fingerprint image(510_No), the method moves to block 513. In block 512, the methodupdates the template repository 518 with the template of the fingerprintimage, and then moves to block 513. In some implementations, the methodperformed in block 328 of FIG. 5 may be performed in block 512.

In block 513, the method determines whether the fingerprint inquiryvalidation phase has been completed. In some implementations, the methodperformed in blocks 316, 318, and 320 of FIG. 5 may be performed inblock 513. If it is determined that the fingerprint inquiry validationphase has been completed (513_Yes), the method ends in block 516.Otherwise, if it is determined that the fingerprint inquiry validationphase has not been completed (513_No), the method moves to block 514.

In block 514, the method provides feedback about the status of theenrollment and/or validation progress to the user, and then moves toblock 502. In some implementations, the methods performed in blocks 322,332, 334, and/or 336 of FIG. 5 may be performed in block 514. Forexample, the method may provide feedback to the user through anapplication layer. The application layer may direct the user to alignfinger in proper orientation. In addition, the application layer maydirect the user to move the finger. The application layer may alsodirect the user to move the finger to get a better coverage of thesensor area as in the case when the fingerprint image is not acceptableas determined in block 504. Moreover, the application layer may providean update of the enrollment and/or validation progress to the user.After a number of successful matches have been identified, a forwardprogress or an enrollment/validation completion message may be shown tothe user. On the other hand, if the fingerprint image is not acceptableas determined in block 504, for example due to insufficient coverage bythe feature keypoints, then the progress bar (not shown) may not advanceor a negative progress may be shown to the user.

FIG. 8A illustrates an example of a set of fingerprint images stored ina template repository. In some implementations, a set of templates thatcorrespond to the set of fingerprint images are stored in the templaterepository. According to aspect of the present disclosure, a templatemay include at least one of: 1) descriptions of feature keypoints; 2)minutiae template; 3) pattern matching template; or any combinationthereof. As shown in FIG. 8A, a set of fingerprint images 602 correspondto a plurality of fingerprint images of a user collected in the templaterepository. In some implementations, each image in the set offingerprint images 602 may represent a section of a single finger of theuser. In some other implementations, the set of fingerprint images 602may represent sections of images collected from multiple fingers fromthe user. FIG. 8B illustrates examples of rejected fingerprint images orthe templates of the rejected fingerprint images that may not be addedto the template repository according to aspects of the presentdisclosure. In the example shown in FIG. 8B, a first fingerprint image604 may be rejected due to insufficient number of feature keypoints inthis fingerprint image. A second fingerprint image 606 may be rejectedbecause it may be a sufficiently overlapped image with respect to theset of fingerprint images 602 of the user in the template repository.

FIG. 9 illustrates an exemplary block diagram of a device that can beconfigured to implement methods of interactive user fingerprintauthentication according to aspects of the present disclosure. A devicemay comprise one or more features of mobile device 700 shown in FIG. 9.In certain embodiments, mobile device 700 may also comprise a wirelesstransceiver 721 which is capable of transmitting and receiving wirelesssignals 723 via wireless antenna 722 over a wireless communicationnetwork. Wireless transceiver 721 may be connected to bus 701 by awireless transceiver bus interface 720. Wireless transceiver businterface 720 may, in some embodiments be at least partially integratedwith wireless transceiver 721. Some embodiments may include multiplewireless transceivers 721 and wireless antennas 722 to enabletransmitting and/or receiving signals according to a correspondingmultiple wireless communication standards such as, for example, versionsof IEEE Std. 802.11, CDMA, WCDMA, LTE, UMTS, GSM, AMPS, Zigbee andBluetooth®, etc.

Mobile device 700 may also comprise SPS receiver 755 capable ofreceiving and acquiring SPS signals 759 via SPS antenna 758. SPSreceiver 755 may also process, in whole or in part, acquired SPS signals759 for estimating a location of a mobile device. In some embodiments,processor(s) 711, memory 740, DSP(s) 712 and/or specialized processors(not shown) may also be utilized to process acquired SPS signals, inwhole or in part, and/or calculate an estimated location of mobiledevice 700, in conjunction with SPS receiver 755. Storage of SPS orother signals may be performed in memory 740 or registers (not shown).

Also shown in FIG. 9, mobile device 700 may comprise digital signalprocessor(s) (DSP(s)) 712 connected to the bus 701 by a bus interface710, processor(s) 711 connected to the bus 701 by a bus interface 710and memory 740. Bus interface 710 may be integrated with the DSP(s) 712,processor(s) 711 and memory 740. In various embodiments, functions maybe performed in response execution of one or more machine-readableinstructions stored in memory 740 such as on a computer-readable storagemedium, such as RAM, ROM, FLASH, or disc drive, just to name a fewexample. The one or more instructions may be executable by processor(s)711, specialized processors, or DSP(s) 712. Memory 740 may comprise anon-transitory processor-readable memory and/or a computer-readablememory that stores software code (programming code, instructions, etc.)that are executable by processor(s) 711 and/or DSP(s) 712 to performfunctions described herein. In a particular implementation, wirelesstransceiver 721 may communicate with processor(s) 711 and/or DSP(s) 712through bus 701 to enable mobile device 700 to be configured as awireless STA as discussed above. Processor(s) 711 and/or DSP(s) 712 mayexecute instructions to execute one or more aspects of processes/methodsdiscussed below in connection with FIG. 10. Processor(s) 711 and/orDSP(s) 712 may perform the methods and/or functions as described inFIGS. 3 through 8A-8B, and 10A-10C.

Also shown in FIG. 9, a user interface 735 may comprise any one ofseveral devices such as, for example, a speaker, microphone, displaydevice, vibration device, keyboard, touch screen, etc. In a particularimplementation, user interface 735 may enable a user to interact withone or more applications hosted on mobile device 700. For example,devices of user interface 735 may store analog or digital signals onmemory 740 to be further processed by DSP(s) 712 or processor 711 inresponse to action from a user. Similarly, applications hosted on mobiledevice 700 may store analog or digital signals on memory 740 to presentan output signal to a user. In another implementation, mobile device 700may optionally include a dedicated audio input/output (I/O) device 770comprising, for example, a dedicated speaker, microphone, digital toanalog circuitry, analog to digital circuitry, amplifiers and/or gaincontrol. In another implementation, mobile device 700 may comprise touchsensors 762 responsive to touching or pressure on a keyboard or touchscreen device.

Mobile device 700 may also comprise a dedicated camera device 764 forcapturing still or moving imagery. Dedicated camera device 764 maycomprise, for example an imaging sensor (e.g., charge coupled device orCMOS imager), lens, analog to digital circuitry, frame buffers, etc. Inone implementation, additional processing, conditioning, encoding orcompression of signals representing captured images may be performed atprocessor 711 or DSP(s) 712. Alternatively, a dedicated video processor768 may perform conditioning, encoding, compression or manipulation ofsignals representing captured images. Additionally, dedicated videoprocessor 768 may decode/decompress stored image data for presentationon a display device (not shown) on mobile device 700.

Mobile device 700 may also comprise sensors 760 coupled to bus 701 whichmay include, for example, inertial sensors and environment sensors.Inertial sensors of sensors 760 may comprise, for example accelerometers(e.g., collectively responding to acceleration of mobile device 700 inthree dimensions), one or more gyroscopes or one or more magnetometers(e.g., to support one or more compass applications). Environment sensorsof mobile device 700 may comprise, for example, temperature sensors,barometric pressure sensors, ambient light sensors, and camera imagers,microphones, just to name few examples. Sensors 760 may generate analogor digital signals that may be stored in memory 740 and processed byDPS(s) or processor 711 in support of one or more applications such as,for example, applications directed to positioning or navigationoperations.

In a particular implementation, mobile device 700 may comprise adedicated modem processor 766 capable of performing baseband processingof signals received and down-converted at wireless transceiver 721 orSPS receiver 755. Similarly, dedicated modem processor 766 may performbaseband processing of signals to be up-converted for transmission bywireless transceiver 721. In alternative implementations, instead ofhaving a dedicated modem processor, baseband processing may be performedby a processor or DSP (e.g., processor 711 or DSP(s) 712).

FIG. 10A illustrates an exemplary flow chart for implementing methods ofinteractive user fingerprint authentication according to aspects of thepresent disclosure. In block 802, the method captures a fingerprintimage of a user. In block 804, the method determines a status offingerprint authentication using the fingerprint image captured. Inblock 806, the method provides interactive feedback to the user inresponse to the status of fingerprint authentication.

FIG. 10B illustrates an exemplary flow chart for implementing methods ofdetermining a status of fingerprint authentication according to aspectsof the present disclosure. In block 812, the method extracts featurekeypoints of the fingerprint image. In block 814, the method determinesfingerprint coverage of the feature keypoints. In block 816, the methodextracts descriptions of the feature keypoints in response to thecoverage of the feature keypoints meet one or more coverage criteria. Inblock 818, the method directs the user to adjust finger location inresponse to the fingerprint coverage of the feature keypoints does notmeet the one or more coverage criteria.

FIG. 10C illustrates another exemplary flow chart for implementingmethods of determining a status of fingerprint authentication accordingto aspects of the present disclosure. In block 822, the method comparesthe template of the fingerprint image captured with the templates of theone or more images in a template repository. According to aspects of thepresent disclosure, a template may include at least one of: 1)descriptions of feature keypoints; 2) minutiae template; 3) patternmatching template; or any combination thereof. In addition, adescription of comparing two images may also include comparing thetemplates of the two images. In block 824, the method determines whetherto update the template repository. According to aspects of the presentdisclosure, the method performed in block 824 may further include themethods performed in block 826, block 828, and block 830. In block 826,the method discards the fingerprint image in response to the fingerprintimage matches one or more images in the template repository. In block828, the method updates the template repository with the template of thefingerprint image in response to the template of the fingerprint imagedoes not match one or more templates of images in the templaterepository and a total number of templates of images in the templaterepository does not exceed a predetermined minimum number of templates.In block 830, the method updates the user about the status offingerprint authentication using a fingerprint authentication progressbar.

According to aspects of the present disclosure, the method may furtherprovide interactive feedback to the user in response to the status offingerprint authentication as shown in block 832 and block 834. In block832, the method directs the user to adjust finger orientation inresponse to the fingerprint image matches the one or more images in thetemplate repository with an incorrect angle. In block 834, the methoddirects the user to adjust finger location in response to thefingerprint image matches the one or more images in the templaterepository with a correct angle.

The methodologies described herein may be implemented by various meansdepending upon applications according to particular examples. Forexample, such methodologies may be implemented in hardware, firmware,software, or combinations thereof. In a hardware implementation, forexample, a processing unit may be implemented within one or moreapplication specific integrated circuits (“ASICs”), digital signalprocessors (“DSPs”), digital signal processing devices (“DSPDs”),programmable logic devices (“PLDs”), field programmable gate arrays(“FPGAs”), processors, controllers, micro-controllers, microprocessors,electronic devices, other devices units designed to perform thefunctions described herein, or combinations thereof.

Some portions of the detailed description included herein are presentedin terms of algorithms or symbolic representations of operations onbinary digital signals stored within a memory of a specific apparatus orspecial purpose computing device or platform. In the context of thisparticular specification, the term specific apparatus or the likeincludes a general purpose computer once it is programmed to performparticular operations pursuant to instructions from program software.Algorithmic descriptions or symbolic representations are examples oftechniques used by those of ordinary skill in the signal processing orrelated arts to convey the substance of their work to others skilled inthe art. An algorithm is here, and generally, is considered to be aself-consistent sequence of operations or similar signal processingleading to a desired result. In this context, operations or processinginvolve physical manipulation of physical quantities. Typically,although not necessarily, such quantities may take the form ofelectrical or magnetic signals capable of being stored, transferred,combined, compared or otherwise manipulated. It has proven convenient attimes, principally for reasons of common usage, to refer to such signalsas bits, data, values, elements, symbols, characters, terms, numbers,numerals, or the like. It should be understood, however, that all ofthese or similar terms are to be associated with appropriate physicalquantities and are merely convenient labels. Unless specifically statedotherwise, as apparent from the discussion herein, it is appreciatedthat throughout this specification discussions utilizing terms such as“processing,” “computing,” “calculating,” “determining” or the likerefer to actions or processes of a specific apparatus, such as a specialpurpose computer, special purpose computing apparatus or a similarspecial purpose electronic computing device. In the context of thisspecification, therefore, a special purpose computer or a similarspecial purpose electronic computing device is capable of manipulatingor transforming signals, typically represented as physical electronic ormagnetic quantities within memories, registers, or other informationstorage devices, transmission devices, or display devices of the specialpurpose computer or similar special purpose electronic computing device.

Wireless communication techniques described herein may be in connectionwith various wireless communications networks such as a wireless widearea network (“WWAN”), a wireless local area network (“WLAN”), awireless personal area network (WPAN), and so on. The term “network” and“system” may be used interchangeably herein. A WWAN may be a CodeDivision Multiple Access (“CDMA”) network, a Time Division MultipleAccess (“TDMA”) network, a Frequency Division Multiple Access (“FDMA”)network, an Orthogonal Frequency Division Multiple Access (“OFDMA”)network, a Single-Carrier Frequency Division Multiple Access (“SC-FDMA”)network, or any combination of the above networks, and so on. A CDMAnetwork may implement one or more radio access technologies (“RATs”)such as cdma2000, Wideband-CDMA (“W-CDMA”), to name just a few radiotechnologies. Here, cdma2000 may include technologies implementedaccording to IS-95, IS-2000, and IS-856 standards. A TDMA network mayimplement Global System for Mobile Communications (“GSM”), DigitalAdvanced Mobile Phone System (“D-AMPS”), or some other RAT. GSM andW-CDMA are described in documents from a consortium named “3rdGeneration Partnership Project” (“3GPP”). Cdma2000 is described indocuments from a consortium named “3rd Generation Partnership Project 2”(“3GPP2”). 3GPP and 3GPP2 documents are publicly available. 4G Long TermEvolution (“LTE”) communications networks may also be implemented inaccordance with claimed subject matter, in an aspect. A WLAN maycomprise an IEEE 802.11x network, and a WPAN may comprise a Bluetooth®network, an IEEE 802.15x, for example. Wireless communicationimplementations described herein may also be used in connection with anycombination of WWAN, WLAN or WPAN.

In another aspect, as previously mentioned, a wireless transmitter oraccess point may comprise a femtocell, utilized to extend cellulartelephone service into a business or home. In such an implementation,one or more mobile devices may communicate with a femtocell via a codedivision multiple access (“CDMA”) cellular communication protocol, forexample, and the femtocell may provide the mobile device access to alarger cellular telecommunication network by way of another broadbandnetwork such as the Internet.

Techniques described herein may be used with an SPS that includes anyone of several GNSS and/or combinations of GNSS. Furthermore, suchtechniques may be used with positioning systems that utilize terrestrialtransmitters acting as “pseudolites”, or a combination of SVs and suchterrestrial transmitters. Terrestrial transmitters may, for example,include ground-based transmitters that broadcast a PN code or otherranging code (e.g., similar to a GPS or CDMA cellular signal). Such atransmitter may be assigned a unique PN code so as to permitidentification by a remote receiver. Terrestrial transmitters may beuseful, for example, to augment an SPS in situations where SPS signalsfrom an orbiting SV might be unavailable, such as in tunnels, mines,buildings, urban canyons or other enclosed areas. Another implementationof pseudolites is known as radio-beacons. The term “SV”, as used herein,is intended to include terrestrial transmitters acting as pseudolites,equivalents of pseudolites, and possibly others. The terms “SPS signals”and/or “SV signals”, as used herein, is intended to include SPS-likesignals from terrestrial transmitters, including terrestrialtransmitters acting as pseudolites or equivalents of pseudolites.

The terms, “and,” and “or” as used herein may include a variety ofmeanings that will depend at least in part upon the context in which itis used. Typically, “or” if used to associate a list, such as A, B or C,is intended to mean A, B, and C, here used in the inclusive sense, aswell as A, B or C, here used in the exclusive sense. Referencethroughout this specification to “one example” or “an example” meansthat a particular feature, structure, or characteristic described inconnection with the example is included in at least one example ofclaimed subject matter. Thus, the appearances of the phrase “in oneexample” or “an example” in various places throughout this specificationare not necessarily all referring to the same example. Furthermore, theparticular features, structures, or characteristics may be combined inone or more examples. Examples described herein may include machines,devices, engines, or apparatuses that operate using digital signals Suchsignals may comprise electronic signals, optical signals,electromagnetic signals, or any form of energy that provides informationbetween locations.

While there has been illustrated and described what are presentlyconsidered to be example features, it will be understood by thoseskilled in the art that various other modifications may be made, andequivalents may be substituted, without departing from claimed subjectmatter. Additionally, many modifications may be made to adapt aparticular situation to the teachings of claimed subject matter withoutdeparting from the central concept described herein. Therefore, it isintended that claimed subject matter not be limited to the particularexamples disclosed, but that such claimed subject matter may alsoinclude all aspects falling within the scope of the appended claims, andequivalents thereof.

What is claimed is:
 1. A method of authenticating an individual,comprising: scanning a portion of a friction-ridge surface of anenrollment finger at a first time to produce a first enrollmenttemplate; moving the enrollment finger; scanning a portion of afriction-ridge surface of the enrollment finger at a second time toproduce a second enrollment template; scanning a portion of afriction-ridge surface of an inquiry finger at a third time to producean inquiry template; producing a first match score by comparing theinquiry template with the first enrollment template; producing a secondmatch score by comparing the inquiry template with the second enrollmenttemplate; mathematically fusing the match scores to produce a compositematch score; comparing the composite match score to an acceptance range;and authenticating the individual if the composite match score is withinthe acceptance range.
 2. The method of claim 1, wherein scanning aportion of a friction-ridge surface of the enrollment finger or theinquiry finger is carried out by an area-array sensor.
 3. The method ofclaim 1, wherein scanning a portion of a friction-ridge surface of theenrollment finger or the inquiry finger is carried out by an ultrasonicsensor.
 4. The method of claim 1, wherein mathematically fusing thematch scores includes multiplying at least one of the match scores by aweighting factor to provide a weighted match score.
 5. The method ofclaim 4, wherein the weighting factor is based on a quality valueassociated with the enrollment template.
 6. The method of claim 5,wherein the quality value associated with the enrollment template isbased on image contrast determined during an enrollment process.
 7. Themethod of claim 5, wherein the quality value associated with theenrollment template is based on a signal-to-noise ratio determinedduring an enrollment process.
 8. The method of claim 4, whereinmathematically fusing the match scores includes adding the weightedmatch score to another weighted match score to produce the compositematch score.
 9. The method of claim 1, wherein authenticating theindividual allows the individual to access an application on a mobiledevice.
 10. The method of claim 1, wherein authenticating the individualallows the individual to use a computer.
 11. A system for authenticatingan individual, comprising: one or more biometric sensors able to obtainenrollment templates corresponding to a friction-ridge surface of anenrollment finger and an inquiry template corresponding to afriction-ridge surface of an inquiry finger; a database in communicationwith the biometric sensor, the database storing enrollment templates;and a computer in communication with the database, the computerprogrammed to: produce a first match score by comparing the inquirytemplate with a first enrollment template; produce a second match scoreby comparing the inquiry template with a second enrollment template;mathematically fuse the match scores to produce a composite match score;compare the composite match score to an acceptance range; andauthenticate the individual if the composite match score is within theacceptance range.
 12. The system of claim 11, wherein the sensor is anarea-array sensor.
 13. The system of claim 11, wherein the sensor is anultrasonic sensor.
 14. The system of claim 11, wherein mathematicallyfusing the match scores includes multiplying at least one of the matchscores by a weighting factor to provide a weighted match score.
 15. Thesystem of claim 14, wherein the weighting factor is based on a qualityvalue associated with the enrollment template.
 16. The system of claim15, wherein the quality value associated with the enrollment template isbased on image contrast determined during an enrollment process.
 17. Thesystem of claim 15, wherein the quality value associated with theenrollment template is based on a signal-to-noise ratio determinedduring an enrollment process.
 18. The system of claim 14, whereinmathematically fusing the match scores includes adding the weightedmatch score to another weighted match score to produce the compositematch score.
 19. The method of claim 11, wherein authenticating theindividual includes allowing the individual to access an application ona mobile device.
 20. The system of claim 11, wherein authenticating theindividual includes allowing the individual to use a computer.
 21. Asystem for authenticating an individual, comprising: means for scanninga portion of a friction-ridge surface of an enrollment finger at a firsttime to produce a first enrollment template, and at a second time toproduce a second enrollment template; means for scanning a portion of afriction-ridge surface of an inquiry finger at a third time to producean inquiry template; means for producing a first match score bycomparing the inquiry template with the first enrollment template andfor producing a second match score by comparing the inquiry templatewith the second enrollment template; means for mathematically fusing thematch scores to produce a composite match score; means for comparing thecomposite match score to an acceptance range; and means forauthenticating the individual if the composite match score is within theacceptance range.
 22. The system of claim 21, wherein the means forscanning a portion of a friction-ridge surface of the enrollment fingeror the means for scanning a portion of a friction-ridge surface of theinquiry finger is an area-array sensor.
 23. The method of claim 21,wherein the means for scanning a portion of a friction-ridge surface ofthe enrollment finger or the means for scanning a portion of afriction-ridge surface of the inquiry finger is an ultrasonic sensor.24. The method of claim 21, wherein the means for mathematically fusingthe match scores multiplies at least one of the match scores by aweighting factor to provide a weighted match score.
 25. The method ofclaim 24, wherein the means for mathematically fusing the match scoresdetermines the weighting factor based on a quality value associated withthe enrollment template.
 26. A non-transitory computer-readable storagemedium having stored thereon instructions for causing a computer to:scan a portion of a friction-ridge surface of an enrollment finger at afirst time to produce a first enrollment template; scan a portion of afriction-ridge surface of the enrollment finger at a second time toproduce a second enrollment template; scan a portion of a friction-ridgesurface of an inquiry finger at a third time to produce an inquirytemplate; produce a first match score by comparing the inquiry templatewith the first enrollment template; produce a second match score bycomparing the inquiry template with the second enrollment template;mathematically fuse the match scores to produce a composite match score;compare the composite match score to an acceptance range; andauthenticate the individual if the composite match score is within theacceptance range.
 27. The non-transitory computer-readable storagemedium of claim 26, wherein the instructions cause the computer toinstruct an area-array sensor to carry out scanning of a portion of afriction-ridge surface of the enrollment finger or the inquiry finger.28. The non-transitory computer-readable storage medium of claim 26,wherein the instructions cause the computer to instruct an ultrasonicsensor to scan a portion of a friction-ridge surface of the enrollmentfinger or the inquiry finger.
 29. The non-transitory computer-readablestorage medium of claim 26, wherein the instructions cause the computerto mathematically fuse the match scores by multiplying at least one ofthe match scores by a weighting factor to provide a weighted matchscore.
 30. The non-transitory computer-readable storage medium of claim29, wherein the instructions cause the computer to determine theweighting factor based on a quality value associated with the enrollmenttemplate.